Open beta · Free for solo devs

Design backends
like a senior architect.
Ship with confidence.

Visual canvas, constraint-aware AI, real-time multi-cloud pricing, and architecture health scoring — all in one collaborative workspace for backend teams.

Start designing free →View live demo
No credit card
3 free diagrams
SSO with GitHub or Google
Ride-sharing Backend · v4
⬡ 74$847/mo
CLIENTmobile / webAPI GATEWAYrate limit · authAUTH SERVICEJWT · OAuthUSER SERVICEprofiles · prefsORDER SERVICErides · trackingPOSTGRESQLRDS · t3.largeREDIS CACHEElastiCacheSQS QUEUEasync jobs!⚠ No DLQ configured
AI Assistantclaude
Design ride-sharing backend for 10k users
BackArch AI
Foundation laid. Your SQS has no DLQ — at 10k req/s you'll lose ~0.1% of messages.
Suggestion
Add circuit breaker between Order → PostgreSQL. Apply →
Monthly Cost
☁ AWS$847
☁ GCP$743
☁ Azure$921
Visual Canvas

The canvas backend
teams have been missing.

Drag, connect, and reason about your system visually. Every component — API gateways to vector DBs — ships pre-wired with correct connection semantics.

40+ componentsTyped connectionsAuto-save + versioning
CLIENTAPI GATEWAYKong · rate limitAuthUsersOrdersPGprimaryComponents+ Lambda+ Kafka
Constraint-First AI

AI that actually understands
your constraints.

Set your budget, cloud preference, traffic, and compliance posture. The AI never suggests $2k/mo Kafka when you're on a $500 budget.

Claude Sonnet-poweredDiagram-aware contextOne-click mutations
BackArch AIclaude-sonnet
☁ AWS💰 $500–2k/mo⚡ 1k req/s👥 3 eng
Add async queue between orders and fulfillment
BackArch AI
Given your $500–2k budget, I'd recommend SQS FIFO(~$24/mo) over Kafka (~$350/mo). I'll add a DLQ and Lambda consumer to keep you serverless.
The Modeling Suite

Beyond boxes and arrows.

Three first-class modeling surfaces for the parts of your system the topology can't capture — behavior, conversations, and data — all stitched to your canvas.

01State Machine Designer

Model behavior, not just boxes.

Draw the states. Simulate the flow. Export to XState in one click.

Every backend has hidden behavior — workflows, lifecycles, status transitions — that boxes-and-arrows diagrams completely miss. The State Machine Designer makes those flows visible, testable, and exportable.

  • Initial / final / choice / fork / join states out of the box
  • Typed transitions with events, guards, and actions
  • Built-in simulator — step through your machine event by event
  • Export to Mermaid, PlantUML, or XState JSON
PENDINGentry / logapproveACTIVEdo / processretryreject / logSIM · step 3 of 5
02Sequence Diagram Editor

Make every conversation legible.

Lifelines, messages, fragments. UML you'll actually want to maintain.

The Sequence Diagram Editor turns service-to-service conversations into a first-class artifact. Capture the exact order of calls, returns, async fan-outs, and error paths — and keep them in sync with your architecture.

  • Actors, services, databases, queues, and external lifelines
  • Sync, async, return, self-call, and create/destroy messages
  • Fragments for alt, loop, opt, and par blocks
  • Export to Mermaid sequenceDiagram or PlantUML
ClientOrderSvcPaymentDBcreateOrder(items)charge(amount)paymentIdnotify{ orderId }alt
03Data Model Designer

Design schema. Ship migrations.

ERDs that compile to PostgreSQL, MySQL, SQLite, Prisma, or TypeScript.

The Data Model Designer is the database canvas your team has been hand-rolling in dbdiagram.io and then losing in Notion. Entities, fields, typed relationships — all version-controlled alongside your architecture.

  • Tables, views, enums, interfaces, and abstract classes
  • Typed fields with constraints, defaults, and indexes
  • 1:1, 1:N, N:M, and inheritance relationships
  • Export to PostgreSQL · MySQL · SQLite · Prisma · TypeScript · Python · Java
User🔑iduuid✉emailvarchar•namevarchar•createdAttimestamp1NOrder🔑iduuid↳userIdfk•totaldecimal•statusenum→ schema.prismaDB · CODE
Architecture Health

Your architecture score,
live as you build.

Every change updates a real-time 0–100 score across resilience, security, scalability, and cost efficiency.

0
/ 100
SPOF detection
Flags services with no redundancy
Missing circuit breakers
Detects unprotected service calls
No DLQ on queues
Your SQS has no dead-letter queue
Observability coverage
Checks for metrics, logs, traces
Auth layer present
Verifies auth on public endpoints
Budget compliance
Flags components over your limit
Design Patterns

Battle-tested patterns,
built right in.

Apply proven patterns in one click. The canvas annotates them visually and explains tradeoffs inline.

40+
Patterns
5
Categories
1-click
Apply to canvas
AI
Tradeoff analysis
Resilience
Circuit Breaker
Stop cascade failures by halting calls to degraded services automatically.
Medium
Use →
Scalability
CQRS
Separate read and write models for independent, elastic scaling.
Hard
Use →
Data
Saga Pattern
Coordinate distributed transactions across microservices without 2PC locks.
Hard
Use →
Networking
API Gateway
Single entry point for all client-to-service communication with auth and rate limiting.
Easy
Use →
State
Event Sourcing
Persist state as an immutable event log for full auditability and time-travel.
Hard
Use →
Resilience
Retry + Backoff
Exponential backoff with jitter for graceful transient-fault recovery.
Easy
Use →
Resilience
Bulkhead
Partition resources so one failing component can't sink the whole system.
Medium
Use →
Resilience
Circuit Breaker
Stop cascade failures by halting calls to degraded services automatically.
Medium
Use →
Scalability
CQRS
Separate read and write models for independent, elastic scaling.
Hard
Use →
Data
Saga Pattern
Coordinate distributed transactions across microservices without 2PC locks.
Hard
Use →
Networking
API Gateway
Single entry point for all client-to-service communication with auth and rate limiting.
Easy
Use →
State
Event Sourcing
Persist state as an immutable event log for full auditability and time-travel.
Hard
Use →
Resilience
Retry + Backoff
Exponential backoff with jitter for graceful transient-fault recovery.
Easy
Use →
Resilience
Bulkhead
Partition resources so one failing component can't sink the whole system.
Medium
Use →
Distributed
Transactional Outbox
Guarantee exactly-once event publishing by writing events in the same DB transaction.
Medium
Use →
Networking
Sidecar Proxy
Run a helper process beside each service for logging, telemetry, and traffic shaping.
Easy
Use →
Migration
Strangler Fig
Replace a legacy system one feature at a time, routing traffic to new services as they ship.
Easy
Use →
Networking
Rate Limiting
Cap requests per client to protect downstream services from overload and abuse.
Easy
Use →
Streaming
Backpressure
Signal producers to slow down when consumers can't keep up — avoid queue collapse.
Hard
Use →
Security
Token Bucket Auth
Stateless auth with rotating JWTs + refresh tokens, scoped per-service.
Medium
Use →
Data
Database per Service
One database per microservice — no shared schemas, no coupling at the storage layer.
Medium
Use →
Distributed
Transactional Outbox
Guarantee exactly-once event publishing by writing events in the same DB transaction.
Medium
Use →
Networking
Sidecar Proxy
Run a helper process beside each service for logging, telemetry, and traffic shaping.
Easy
Use →
Migration
Strangler Fig
Replace a legacy system one feature at a time, routing traffic to new services as they ship.
Easy
Use →
Networking
Rate Limiting
Cap requests per client to protect downstream services from overload and abuse.
Easy
Use →
Streaming
Backpressure
Signal producers to slow down when consumers can't keep up — avoid queue collapse.
Hard
Use →
Security
Token Bucket Auth
Stateless auth with rotating JWTs + refresh tokens, scoped per-service.
Medium
Use →
Data
Database per Service
One database per microservice — no shared schemas, no coupling at the storage layer.
Medium
Use →
Templates

Production architectures,
cloned in seconds.

Don't start from a blank canvas. Clone a battle-tested system — full nodes, edges, and AI context included — then tweak it for your stack.

20+
System templates
1-click
Clone to canvas
Full
Nodes + edges + AI
Editable
Tweak freely
ClientAPIRedisHasher λDynamoDBAnalytics
🔗
ClassicServerless

URL Shortener

Hashing, caching, redirect tracking, and analytics — the system-design starter every team should know.

9nodes
94health
AIcontext ready
Use this template →
Live Multi-Cloud Pricing

Know the real cost
before you provision anything.

Pick a workload below — watch every cloud's monthly bill recompute in real time. Same engine, live for every component you place on the canvas.

AWS
Amazon AWS
$847/mo
↑ $104 vs GCP
EC2 t3.large$168
RDS PostgreSQL$384
ElastiCache$165
SQS + Lambda$130
CHEAPEST
GCP
Google Cloud
$743/mo
↓ best price · saves $178/mo
Compute n2$142
Cloud SQL$348
Memorystore$143
Pub/Sub + Run$110
AZ
Microsoft Azure
$921/mo
↑ $178 vs GCP
VM D2s v3$191
Azure SQL$412
Azure Cache$178
Service Bus$140
Monthly spend — ride-sharing backend
AWS
$847
$847
GCP
$743
$743
AZ
$921
$921
AI model pricing
claude-sonnet-4-6Recommended$3 / $15 MTok
claude-haiku-4-5Fastest$0.80 / $4 MTok
gpt-4oOpenAI$2.50 / $10 MTok
gemini-2.0-flashGoogle$0.10 / $0.40 MTok
✦
BackArch AI: For a ride-sharing workload, Google Cloud wins at $743/mo— that's $2,136/yr cheaper than the most expensive option. Click a workload chip above to see how the math shifts.
See subscription plans →Explore pricing explorer
Coming Soonon the roadmap
Real-time Collaboration

Your whole team,
on the same canvas.

See teammates' cursors, selections, and edits live. Built on Y.js CRDTs — no merge conflicts, no lock contention. Just flow.

Y.js CRDT engineLive presence cursorsMultiplayer awareness
AKSRJM3 collaborators · liveAPI GatewayKongUser ServicePostgreSQLAlexSamJordanRedis Cache
Get started today

Architecture clarity
in 2 minutes.

Start from a template or let the AI generate your first architecture.
No credit card. No setup. No nonsense.

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Free forever · 3 diagrams · SSO with GitHub or Google